Impact of the COVID-19 pandemic on breast cancer screening indicators in a Spanish population-based program: a cohort study

  1. Guillermo Bosch
  2. Margarita Posso
  3. Javier Louro
  4. Marta Roman
  5. Miquel Porta
  6. Xavier Castells
  7. Francesc Macià

  • Curated by eLife

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    Evaluation Summary:

    This paper will be of interest to public health specialists and cancer scientists working in cancer prevention. The work presents valuable data on how the COVID-19 pandemic has impacted breast cancer screening indicators compared with previous years. Overall, the results support the assertion that while many key indicators have not been substantially impacted, the screening participation rate declined and fewer cancers were screen-detected in 2020-21.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

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Abstract

To assess the effect of the COVID-19 pandemic on performance indicators in the population-based breast cancer screening program of Parc de Salut Mar (PSMAR), Barcelona, Spain.

Methods:

We conducted a before-and-after, study to evaluate participation, recall, false positives, the cancer detection rate, and cancer characteristics in our screening population from March 2020 to March 2021 compared with the four previous rounds (2012–2019). Using multilevel logistic regression models, we estimated the adjusted odds ratios (aORs) of each of the performance indicators for the COVID-19 period, controlling by type of screening (prevalent or incident), socioeconomic index, family history of breast cancer, and menopausal status. We analyzed 144,779 invitations from 47,571women.

Results:

During the COVID-19 period, the odds of participation were lower in first-time invitees (aOR = 0.90 [95% CI = 0.84–0.96]) and in those who had previously participated regularly and irregularly (aOR = 0.63 [95% CI = 0.59–0.67] and aOR = 0.95 [95% CI = 0.86–1.05], respectively). Participation showed a modest increase in women not attending any of the previous rounds (aOR = 1.10 [95% CI = 1.01–1.20]). The recall rate decreased in both prevalent and incident screening (aOR = 0.74 [95% CI = 0.56–0.99] and aOR = 0.80 [95% CI = 0.68–0.95], respectively). False positives also decreased in both groups (prevalent aOR = 0.92 [95% CI = 0.66–1.28] and incident aOR = 0.72 [95% CI = 0.59–0.88]). No significant differences were observed in compliance with recall (OR = 1.26, 95% CI = 0.76–2.23), cancer detection rate (aOR = 0.91 [95% CI = 0.69–1.18]), or cancer stages.

Conclusions:

The COVID-19 pandemic negatively affected screening attendance, especially in previous participants and newcomers. We found a reduction in recall and false positives and no marked differences in cancer detection, indicating the robustness of the program. There is a need for further evaluations of interval cancers and potential diagnostic delays.

Funding:

This study has received funding by grants PI19/00007 and PI21/00058, funded by Instituto de Salud Carlos III (ISCIII) and cofunded by the European Union and Grant RD21/0016/0020 funded by Instituto de Salud Carlos III and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR).

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  1. Version published to 10.7554/elife.77434 on eLife
  2. eLife

    Evaluation Summary:

    This paper will be of interest to public health specialists and cancer scientists working in cancer prevention. The work presents valuable data on how the COVID-19 pandemic has impacted breast cancer screening indicators compared with previous years. Overall, the results support the assertion that while many key indicators have not been substantially impacted, the screening participation rate declined and fewer cancers were screen-detected in 2020-21.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    This study aims to examine how the COVID-19 pandemic has impacted cancer screening services, more specifically breast cancer screening in Spain using a number of key program performance indicators. They show that some performance indicators (screening participation, number of screen-detected cancers) were impacted, but that many others appear to be unchanged (false positive rates, cancer detection rates per participant, cancer stage distribution). Overall, this study adds important data to examine the question of how the pandemic has impacted cancer services.

    The major strengths of this study include its large representative sample size, the use of multiple rounds of screening in the pre-COVID-19 era to establish a pre-pandemic baseline, and the ability to adjust for several demographic and socioeconomic indicators that could confound results.

    Overall, the results support the study's conclusions that the COVID-19 pandemic negatively affected screening attendance, especially in previous participants and newcomers, but that other indicators such as false-positives rates, cancer detection rates per participant did not change. I think it is possible there is even evidence the recall rate is lower in the post-COVID-19 era; this analysis did not achieve statistical significance in stratified analyses, but I think that if the authors were to do an overall analysis of all participants they would find a significantly lower recall rate in the post-COVID-19 era. I think that the analysis of the changes of distributions of characteristics of participants in the post-COVID-19 era (Table 2) is not as informative as it could be, as participation rates by socioeconomic characteristics are influenced by invitation rates, and the invitation rates are shown to have varied over time. It is therefore possible that changes in the sociodemographic characteristics of participants in the post-COVID-19 era represent changes in eligibility to the program rather than changes in participation rates by socioeconomic status. I would have liked to see an analysis of participation rates (participants/invitations) by socioeconomic variables to better support the authors' conclusions.

    This data and analysis will be useful for other countries with breast screening programs who will be looking to compare the impact of the pandemic has had on their own screening programs.

  4. eLife

    Reviewer #2 (Public Review):

    The paper presents a description of the changes of the screening performance indicators during the period March 2020 to March 2021 compared to the period 2021-2019. The authors found a decrease in screening attendance, particularly in women who previously participated and in newcomers. On the other hand, the indicators focusing on the accuracy of the screening test (cancer detection, recall and false positives) showed small differences, if any.

    The data are interesting, but a more detailed analysis of the mechanisms underlying the changes would be much more informative and useful: what was the flow of invitations? Did reduced participation occur in delayed invitations? Can you estimate the delay in mammography? Is there an association between delay in invitation and attendance?

    The paper is very well presented with a robust set of indicators. Interpretation of the results is sound.

    The analyses could be improved by trying to understand the mechanisms that caused the decrease in attendance.

  5. eLife

    Reviewer #3 (Public Review):

    The authors studied the effect of the COVID-19 pandemic on some performance indicators in the population-based breast cancer screening programme of Barcelona, Spain. Towards this goal, they conducted a before and after analysis comparing the performance of the screening indicators before and after the pandemic and controlling for some characteristics of the screening population such as type of breast cancer screening round (prevalent, incidence), socioeconomic index, family history of breast cancer. The authors highlighted a reduction in participation in the post COVID-19 period especially in women invited for the first time or in those who had already participated in screening in previous years. The analysis did not reveal significant differences in other performance parameters (recall rate, detection rate, false positives, stage of tumors). The study has public health merit in starting to evaluate (with real numbers) the impact that such a disastrous event as the COVID-19 pandemic has had on screening activities. And, above all, to begin to evaluate the impact in order to implement countermeasures and strategies to resolve the critical issues that have unequivocally occurred as a consequence of the interruption/slowdown of breast cancer screening activities.

  6. ScreenIT

    SciScore for 10.1101/2022.03.04.22271911: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    SPSS version 25 software was used for the creation and validation of the database and recodification of variables, while statistical software R version 3.5.0 (Development Core Team, 2014) was used for the logistic regression models.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has some limitations. First, we used pseudo-anonymized data and analyzed each invitation as an independent measurement, although a single woman can have more than one invitation. Nevertheless, we considered four groups of type of screening rounds to evaluate attendance, mitigating the fact that the measurements were not truly independent, although this study treated them as though they were. Second, the number of cancers detected during the pandemic period was relatively low, which limited the statistical power of our results. Our study also has some strengths. To our best knowledge, most of the observational evidence assessing the effect of the pandemic compared screening indicators with the previous year (33–35). In contrast, we included a long period of four previous rounds (eight years) of invitations for the same target population. We took this longitudinal approach since it is known that there are fluctuations in participation and cancer detection that may depend on time (36). Therefore, our approach provides information on the pandemic beyond these common fluctuations In conclusion, our findings suggest that the impact of the pandemic on screening attendance depends on the type of screening, with women who regularly participate being the most affected. Targeting this specific population with a proactive invitation could be a way to ensure the historically higher participation in this group. Despite this, we should not forget other groups that attended screeni...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  7. Version published to 10.1101/2022.03.04.22271911v1 on medRxiv